data("cars")
median(cars$speed)## [1] 15On_Time_Performance <- read.csv("~/Downloads/Mini Project-2/On_Time_Performance.csv", header=FALSE)
head(On_Time_Performance)## V1 V2 V3 V4 V5 V6 V7 V8
## 1 Year Quarter Month DayofMonth DayOfWeek FlightDate UniqueCarrier AirlineID
## 2 2018 1 1 16 2 2018-01-16 AA 19805
## 3 2018 1 1 17 3 2018-01-17 AA 19805
## 4 2018 1 1 18 4 2018-01-18 AA 19805
## 5 2018 1 1 19 5 2018-01-19 AA 19805
## 6 2018 1 1 20 6 2018-01-20 AA 19805
## V9 V10 V11 V12 V13
## 1 Carrier TailNum FlightNum OriginAirportID OriginAirportSeqID
## 2 AA N128AN 228 12892 1289206
## 3 AA N128AN 228 12892 1289206
## 4 AA N121AN 228 12892 1289206
## 5 AA N129AA 228 12892 1289206
## 6 AA N133AN 228 12892 1289206
## V14 V15 V16 V17 V18
## 1 OriginCityMarketID Origin OriginCityName OriginState OriginStateFips
## 2 32575 LAX Los Angeles, CA CA 06
## 3 32575 LAX Los Angeles, CA CA 06
## 4 32575 LAX Los Angeles, CA CA 06
## 5 32575 LAX Los Angeles, CA CA 06
## 6 32575 LAX Los Angeles, CA CA 06
## V19 V20 V21 V22 V23
## 1 OriginStateName OriginWac DestAirportID DestAirportSeqID DestCityMarketID
## 2 California 91 12173 1217303 32134
## 3 California 91 12173 1217303 32134
## 4 California 91 12173 1217303 32134
## 5 California 91 12173 1217303 32134
## 6 California 91 12173 1217303 32134
## V24 V25 V26 V27 V28 V29 V30
## 1 Dest DestCityName DestState DestStateFips DestStateName DestWac CRSDepTime
## 2 HNL Honolulu, HI HI 15 Hawaii 2 2011
## 3 HNL Honolulu, HI HI 15 Hawaii 2 2011
## 4 HNL Honolulu, HI HI 15 Hawaii 2 2011
## 5 HNL Honolulu, HI HI 15 Hawaii 2 2011
## 6 HNL Honolulu, HI HI 15 Hawaii 2 2011
## V31 V32 V33 V34 V35 V36
## 1 DepTime DepDelay DepDelayMinutes DepDel15 DepartureDelayGroups DepTimeBlk
## 2 2010 -1.00 0.00 0.00 -1 2000-2059
## 3 2003 -8.00 0.00 0.00 -1 2000-2059
## 4 2008 -3.00 0.00 0.00 -1 2000-2059
## 5 2010 -1.00 0.00 0.00 -1 2000-2059
## 6 2001 -10.00 0.00 0.00 -1 2000-2059
## V37 V38 V39 V40 V41 V42 V43 V44
## 1 TaxiOut WheelsOff WheelsOn TaxiIn CRSArrTime ArrTime ArrDelay ArrDelayMinutes
## 2 24.00 2034 2358 7.00 0029 0005 -24.00 0.00
## 3 18.00 2021 2348 5.00 0029 2353 -36.00 0.00
## 4 14.00 2022 0006 6.00 0029 0012 -17.00 0.00
## 5 17.00 2027 2352 3.00 0029 2355 -34.00 0.00
## 6 17.00 2018 2352 5.00 0029 2357 -32.00 0.00
## V45 V46 V47 V48 V49 V50
## 1 ArrDel15 ArrivalDelayGroups ArrTimeBlk Cancelled CancellationCode Diverted
## 2 0.00 -2 0001-0559 0.00 0.00
## 3 0.00 -2 0001-0559 0.00 0.00
## 4 0.00 -2 0001-0559 0.00 0.00
## 5 0.00 -2 0001-0559 0.00 0.00
## 6 0.00 -2 0001-0559 0.00 0.00
## V51 V52 V53 V54 V55 V56
## 1 CRSElapsedTime ActualElapsedTime AirTime Flights Distance DistanceGroup
## 2 378.00 355.00 324.00 1.00 2556.00 11
## 3 378.00 350.00 327.00 1.00 2556.00 11
## 4 378.00 364.00 344.00 1.00 2556.00 11
## 5 378.00 345.00 325.00 1.00 2556.00 11
## 6 378.00 356.00 334.00 1.00 2556.00 11
## V57 V58 V59 V60 V61
## 1 CarrierDelay WeatherDelay NASDelay SecurityDelay LateAircraftDelay
## 2
## 3
## 4
## 5
## 6
## V62 V63 V64 V65 V66
## 1 FirstDepTime TotalAddGTime LongestAddGTime DivAirportLandings DivReachedDest
## 2 0
## 3 0
## 4 0
## 5 0
## 6 0
## V67 V68 V69 V70 V71
## 1 DivActualElapsedTime DivArrDelay DivDistance Div1Airport Div1AirportID
## 2
## 3
## 4
## 5
## 6
## V72 V73 V74 V75 V76
## 1 Div1AirportSeqID Div1WheelsOn Div1TotalGTime Div1LongestGTime Div1WheelsOff
## 2
## 3
## 4
## 5
## 6
## V77 V78 V79 V80 V81
## 1 Div1TailNum Div2Airport Div2AirportID Div2AirportSeqID Div2WheelsOn
## 2
## 3
## 4
## 5
## 6
## V82 V83 V84 V85 V86
## 1 Div2TotalGTime Div2LongestGTime Div2WheelsOff Div2TailNum Div3Airport
## 2
## 3
## 4
## 5
## 6
## V87 V88 V89 V90 V91
## 1 Div3AirportID Div3AirportSeqID Div3WheelsOn Div3TotalGTime Div3LongestGTime
## 2
## 3
## 4
## 5
## 6
## V92 V93 V94 V95 V96
## 1 Div3WheelsOff Div3TailNum Div4Airport Div4AirportID Div4AirportSeqID
## 2
## 3
## 4
## 5
## 6
## V97 V98 V99 V100 V101
## 1 Div4WheelsOn Div4TotalGTime Div4LongestGTime Div4WheelsOff Div4TailNum
## 2
## 3
## 4
## 5
## 6
## V102 V103 V104 V105 V106
## 1 Div5Airport Div5AirportID Div5AirportSeqID Div5WheelsOn Div5TotalGTime
## 2
## 3
## 4
## 5
## 6
## V107 V108 V109 V110
## 1 Div5LongestGTime Div5WheelsOff Div5TailNum NA
## 2 NA
## 3 NA
## 4 NA
## 5 NA
## 6 NAsum(is.na(On_Time_Performance$WheelsOff))## [1] 0library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, uniondata <- read.csv("~/Downloads/Mini Project-2/On_Time_Performance.csv")
colnames(On_Time_Performance)## [1] "V1" "V2" "V3" "V4" "V5" "V6" "V7" "V8" "V9" "V10"
## [11] "V11" "V12" "V13" "V14" "V15" "V16" "V17" "V18" "V19" "V20"
## [21] "V21" "V22" "V23" "V24" "V25" "V26" "V27" "V28" "V29" "V30"
## [31] "V31" "V32" "V33" "V34" "V35" "V36" "V37" "V38" "V39" "V40"
## [41] "V41" "V42" "V43" "V44" "V45" "V46" "V47" "V48" "V49" "V50"
## [51] "V51" "V52" "V53" "V54" "V55" "V56" "V57" "V58" "V59" "V60"
## [61] "V61" "V62" "V63" "V64" "V65" "V66" "V67" "V68" "V69" "V70"
## [71] "V71" "V72" "V73" "V74" "V75" "V76" "V77" "V78" "V79" "V80"
## [81] "V81" "V82" "V83" "V84" "V85" "V86" "V87" "V88" "V89" "V90"
## [91] "V91" "V92" "V93" "V94" "V95" "V96" "V97" "V98" "V99" "V100"
## [101] "V101" "V102" "V103" "V104" "V105" "V106" "V107" "V108" "V109" "V110"avg_delay_by_carrier <- data %>%
group_by(Carrier) %>%
summarise(avg_departure_delay = mean(DepDelay, na.rm = TRUE))
avg_delay_by_carrier## # A tibble: 18 × 2
## Carrier avg_departure_delay
## <chr> <dbl>
## 1 9E 12.4
## 2 AA 6.93
## 3 AS -2.25
## 4 B6 20.4
## 5 DL 9.74
## 6 EV 13.6
## 7 F9 16.0
## 8 G4 10.4
## 9 HA 1.72
## 10 MQ 8.82
## 11 NK 5.61
## 12 OH 13.8
## 13 OO 15.1
## 14 UA 5.87
## 15 VX 2.83
## 16 WN 8.03
## 17 YV 8.86
## 18 YX 7.26largest_delay_by_carrier <- avg_delay_by_carrier %>%
arrange(desc(avg_departure_delay)) %>%
head(1)
largest_delay_by_carrier## # A tibble: 1 × 2
## Carrier avg_departure_delay
## <chr> <dbl>
## 1 B6 20.4library(jsonlite)
library(httr)
url <- "https://min-api.cryptocompare.com/data/v2/histoday?fsym=BTC&tsym=USD&limit=100"
data <- fromJSON(url)
ohlcv_data <-data$Data$Data
close_prices <- ohlcv_data$close
str(close_prices)## num [1:101] 91904 95958 95670 97511 96474 ...closse_prices <- as.numeric(close_prices)
max_close_price <- max(close_prices, na.rm = TRUE)
max_close_price## [1] 106155.6